Microsoft Technology Licensing, LLC

Karen Jensen

George E Heidorn

William B Dolan

Stephen D Richardson

John J Messerly

Steve Richardson

David Earl Heckerman

Eric I Horvitz

Lucretia Henrica Vanderwende

John S Breese

James Randall Flynn

Samuel D Hobson

Gregory L Shaw

Erich-So Slashedren Finkelstein

A lexical knowledge base is compiled automatically from a machine-readable source (such as an on-line dictionary or unstructured text). The preferred embodiment of the invention makes use of 'backward linking,' by which inverse semantic relations are discerned from the text and used to augment the knowledge base. By this arrangement, on-line dictionaries and other texts can provide formidable sources of 'common sense' knowledge about the world.

Method and system for compiling a lexical knowledge base

The present invention is directed to performing information retrieval utilizing semantic representation of text. In a preferred embodiment, a tokenizer generates from an input string information retrieval tokens that characterize the semantic relationship expressed in the input string. The tokenizer first creates from the input string a primary logical form characterizing a semantic relationship between selected words in the input string. The tokenizer then identifies hypemyms that each have an &ldquo;is a&rdquo; relationship with one of the selected words in the input string. The tokenizer then constructs from the primary logical form one or more alternative logical forms. The tokenizer constructs each alternative logical form by, for each of one or more of the selected words in the input string, replacing the selected word in the primary logical form with an identified hypernym of the selected word. Finally, the tokenizer generates tokens representing both the primary logical form and the alternative logical forms. The tokenizer is preferably used to generate tokens for both constructing an index representing target documents and processing a query against that index.

Information retrieval utilizing semantic representation of text and based on constrained expansion of query words

The present invention is directed to performing information retrieval utilizing semantic representation of text. In a preferred embodiment, a tokenizer generates from an input string information retrieval tokens that characterize the semantic relationship expressed in the input string. The tokenizer first creates from the input string a primary logical form characterizing a semantic relationship between selected words in the input string. The tokenizer then identifies hypernyms that each have an 'is a' relationship with one of the selected words in the input string. The tokenizer then constructs from the primary logical form one or more alternative logical forms. The tokenizer constructs each alternative logical form by, for each of one or more of the selected words in the input string, replacing the selected word in the primary logical form with an identified hypernym of the selected word. Finally, the tokenizer generates tokens representing both the primary logical form and the alternative logical forms. The tokenizer is preferably used to generate tokens for both constructing an index representing target documents and processing a query against that index.

Information retrieval utilizing semantic representation of text by

A method and system that uses a chunking technique to guide the parsing. A chunk is a portion of the input for which the system has determined that a sufficient number of syntax rules have been applied such that further application of syntax rules to that chunk is unlikely to produce a more accurate sub-parse for that chunk. When using the chunking technique, the system selects a syntax rule to apply to the current partial parse (sub-trees) of the input sentence. The selected syntax rule has a high probability relative to other syntax rules that can be applied to the one or more potential sub-trees of the input sentence. The system then applies the selected syntax rule to the potential sub-trees of the input sentence to form a new potential sub-trees of the input sentence. When the system determines that syntax rules with low probabilities have recently been applied, the system disables application of syntax rules to a portion of parse of the input sentence (i.e., a chunk) so that that syntax rules can be applied to the other portion of the input sentence.

Method and system for natural language parsing using chunking

Information retrieval utilizing semantic representation of text

Methods and computer systems for semantically analyzing natural language sentences. The natural language processing subsystems for morphological and syntactic analysis transform an input sentence into a syntax parse tree. Semantic analysis applies three sets of semantic rules to create a skeletal logical form graph from a syntax parse tree. Semantic analysis then applies two additional sets of semantic rules to provide semantically meaningful labels for the links of the logical form graph, to create additional logical form graph nodes for missing elements, and to unify redundant elements. The final logical form graph represents the complete semantic analysis of an input sentence.

Method and system for computing semantic logical forms from syntax trees

A method and system for determining the likelihood that a certain syntax rule when applied to a partial parse of an input will produce a node that will be part of the correct parse for the input. Each syntax rule indicates a higher-level syntactic construct that can be formed from one or more lower-level syntactic constructs. Each syntax rule has a probability which indicates the likelihood that the syntax rule will succeed and produce a node in the resulting parse tree. Each syntax rule also has a heuristic score formula indicating how to calculate a heuristically derived score for the higher-level syntactic construct created when the syntax rule is successfully applied. When a syntax rule is successfully applied while parsing the input sentence, the system calculates a probability for the higher-level syntactic construct produced by the syntax rule. The system then calculates a heuristic score for the higher-level syntactic construct produced by the syntax rule based on the heuristic score formula of the syntax rule and the calculated heuristic scores of the lower-level syntactic constructs to which the syntax rule was successfully applied. The system then combines the calculated probabilities and the calculated heuristic scores to guide the selecting of syntax rules to apply.

Method and system for natural language parsing using podding

An improved free text query method and system is provided as part of an improved on-line help system. In a preferred embodiment of the present invention, the on-line help system provides a free text query system that performs partial analysis. The partial analysis performed by the preferred embodiment includes identifying keywords within input provided by the user, performing disambiguation analysis, performing definiteness analysis, performing capitalization analysis, and generating a ranked list of candidates according to a probability associated with each candidate. In addition, the preferred embodiment of the present invention is internationalizable. That is, the present invention is easily ported between different languages.

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Bellevue, WA, United States of America

Karen Jensen